Dynamics of electric bike ownership and use in Kunming, China. (January 2016)

• Record Type: Journal Article
• Authors: Cherry, Christopher R.; Yang, Hongtai; Jones, Luke R.; He, Min
• Is Part Of: Transport policy. Volume 45(2016)
• Page Start: 127
• Page End: 135
• Publication Date: 2016-01
• Subjects: Electric bicycle -- e-bike -- Electric scooter -- China -- Mode shift -- Motorization; Transportation and state -- Periodicals; Transportation -- Rates -- Periodicals; 388
• DOI: 10.1016/j.tranpol.2015.09.007
• Languages: English
• ISSNs: 0967-070X

Abstract

Abstract: The rapid adoption of electric bikes (e-bikes) (~150 million in 10 years) has come with debate over their role in China's urban transportation system. While there has been some research quantifying impacts of e-bikes on the transportation system, there has been little work tracking e-bike use patterns over time. This paper investigates e-bike use over a 6-year period. Four bi-annual travel diary surveys of e-bike users were conducted between 2006 and 2012 in Kunming, China. Choice models were developed to investigate factors influencing mode-transition and motorization pathways. As expected, income and vehicle ownership strongly influence car-based transitions. Younger and female respondents were more likely to choose car-based modes. Systematic and unobserved changes over time (time-dynamics) favor car-based modes, with the exception of previous car users who already shifted away from cars being less likely to revert to cars over time. E-bikes act as an intermediate mode, interrupting the transition from bicycle to bus and from bus to car. Over 6 years, e-bikes are displacing prospective bus (65→55%), car/taxi (15→24%) and bicycle (19→7%) trips. Over 40% of e-bike riders now have household car access so e-bikes are effectively replacing many urban car trips. Highlights: About half of e-bike riders are substituted bus riders. About one quarter of e-bike riders are substituted car users. Most e-bike riders would not shift to bicycles. E-bike policy (supportive/restrictive) should consider mode shift impacts. High incomes and education levels dominate the transition to higher car use.